Special Fault Tolerant properties of FFT-based transform domain Adaptive Filters

Transform domain fault tolerant adaptive filters (FTAFs) rely on inherent learning capabilities of the adaptive process to compensate for transient (soft) or permanent (hard) errors in the hardware implementation. In this paper it is shown that an FFT-based transform domain FTAF operating on real valued signals can provide a considerable degree of fault tolerance without introducing redundant hardware. When the filter operates on real valued signals the added complexity of complex arithmetic provides additional fault tolerant capabilities that may be useful for adaptive filters implemented in highly scaled nano-technology circuits where soft and hard errors are of increasing concern.